Data Standardization

By | September 18, 2017

A critical step to ensure easy data integration across the enterprise is adopting a solid Data Standardization approach.

This will ensure that your data is easier to match and integrate, regardless of the source systems. Even with today’s advanced Fuzzy Data Matching technologies it is still much easier and more reliable when the data is presented in a more structured and easily comparable standard.

A good example of Data Standardization is to separate the address elements into different Fields rather than grouping all this data into a single field.

For example:

Address: “Venture House, Arlington Square, Downshire Way, Bracknell, Berks, RG12 1WA” would be better standardized as:

Building Number/Name: “Venture House”
Address1: “Arlington Square”
Address2: “Downshire Way”
City: “Bracknell”
County: “Berks”
Postal Code: “RG12 1WA”

This standardization will make it easier for you to maintain the quality of the data, and to easily integrate the data throughout your organisation.

Another example is people’s names, it is much easier to work with peoples names when they are broken into their constituent parts; rather than store the entire name within a single field, for example: Title, First Name, Middle Name, Last Name, and Prefix.

Obviously, if you can implement the same standards across all your systems then you will have considerable advantages when it comes to maintaining your data quality, and integrating your data.

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